Whole genome sequence analysis of low-density lipoprotein cholesterol across 246 K individuals.
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Selvaraj Margaret Sunitha, Li Xihao, Li Zilin, Van Buren Eric, Haidermota Sara, Postupaka Darina, Hornsby Whitney, Bis Joshua C, Brody Jennifer A, Cade Brian E, Chung Ren-Hua, Curran Joanne E, Damrauer Scott M, de Las Fuentes Lisa, de Vries Paul S, Duggirala Ravindranath, Freedman Barry I, Graff MariaElisa, Guo Xiuqing, Hidalgo Bertha A, Hou Lifang, Irvin Ryan, Judy Renae, Kalyani Rita R, Kelly Tanika N, Konigsberg Iain R, Kral Brian G, Kwee Lydia Coulter, Levy Daniel, Li Changwei, Manichaikul Ani W, Martin Lisa Warsinger, Montasser May E, Morrison Alanna C, Naseri Take, North Kari E, O'Connell Jeffrey R, Palmer Nicholette D, Peyser Patricia A, Reiner Alex P, Shah Svati H, Smit Roelof A J, Smith Jennifer A, Taylor Kent D, Tiwari Hemant, Tsai Michael Y, Viali Satupa'itea, Wang Zhe, Wang Yuxuan, Zhao Wei, Arnett Donna K, Blangero John, Boerwinkle Eric, Bowden Donald W, Carlson Jenna C, Chen Yii-Der Ida, Ellinor Patrick T, Fornage Myriam, He Jiang, Heard-Costa Nancy, Kaplan Robert C, Kardia Sharon L R, Kooperberg Charles, Kraus William E, Lange Leslie A, Loos Ruth J F, Mitchell Braxton D, Psaty Bruce M, Rader Daniel J, Redline Susan, Rich Stephen S, Yanek Lisa R, Gibbs Richard, Gabriel Stacey, Viaud-Martinez Karine A, Dutcher Susan K, Germer Soren, Kim Ryan, Rotter Jerome I, Lin Xihong, Peloso Gina M, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Natarajan Pradeep
Аннотация
RESULTS: Here, we conduct the largest meta-analysis of whole genome sequencing for low-density lipoprotein cholesterol (LDL-C), a therapeutic target for coronary artery disease, analyzing data from 246 K participants and integrating 1.23B variants from the UK Biobank and the Trans-Omics for Precision Medicine (TOPMed) program. We identify numerous rare coding and non-coding gene associations related to LDL-C, with replication across 86 K participants in All of Us. Our findings are based on single-variant analyses, rare coding and non-coding variant aggregation tests, and sliding window approaches. Through this comprehensive analysis, we identify 704 novel single-variant associations, 25 novel rare coding variant aggregates, 28 novel rare non-coding variant aggregates, and one novel sliding window aggregate.
CONCLUSIONS: This study provides a meta-analysis framework for large-scale whole genome sequence association analyses from diverse population groups, yielding novel rare non-coding variant associations.